Musical Experience, Auditory Perception and Reading

Musical Experience, Auditory Perception and Reading-Related Skills in ChildrenKaren Banai1*, Merav Ahissar2

1 Department of Communication Sciences and Disorders, University of Haifa, Haifa, Israel, 2 Departments of Psychology and Cognitive Sciences, HebrewUniversity, Jerusalem, Israel

Abstract

Background: The relationships between auditory processing and reading-related skills remain poorly understooddespite intensive research. Here we focus on the potential role of musical experience as a confounding factor.Specifically we ask whether the pattern of correlations between auditory and reading related skills differ betweenchildren with different amounts of musical experience.Methodology/Principal Findings: Third grade children with various degrees of musical experience were tested on abattery of auditory processing and reading related tasks. Very poor auditory thresholds and poor memory skills wereabundant only among children with no musical education. In this population, indices of auditory processing(frequency and interval discrimination thresholds) were significantly correlated with and accounted for up to 13% ofthe variance in reading related skills. Among children with more than one year of musical training, auditoryprocessing indices were better, yet reading related skills were not correlated with them. A potential interpretation forthe reduction in the correlations might be that auditory and reading-related skills improve at different rates as afunction of musical training.Conclusions/Significance: Participants’ previous musical training, which is typically ignored in studies assessingthe relations between auditory and reading related skills, should be considered. Very poor auditory and memory skillsare rare among children with even a short period of musical training, suggesting musical training could have animpact on both. The lack of correlation in the musically trained population suggests that a short period of musicaltraining does not enhance reading related skills of individuals with within-normal auditory processing skills. Furtherstudies are required to determine whether the associations between musical training, auditory processing andmemory are indeed causal or whether children with poor auditory and memory skills are less likely to study musicand if so, why this is the case.

Citation: Banai K, Ahissar M (2013) Musical Experience, Auditory Perception and Reading-Related Skills in Children. PLoS ONE 8(9): e75876. doi:10.1371/journal.pone.0075876

Editor: Joel Snyder, UNLV, United States of America

Received April 30, 2013; Accepted August 16, 2013; Published September 24, 2013

Copyright: © 2013 Banai et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The study was supported by the Israeli Science Foundation. The funders had no role in study design, data collection and analysis, decision topublish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Auditory processing has been proposed to play a role in thedevelopment of reading (e.g., [1,2]), because learning to readrequires linking the sounds of spoken language with theirwritten forms (see 3). Nevertheless, the role of auditoryprocessing in reading and reading-related language skillsremains debated despite the many studies attempting to clarifyit. One source of difficulty is the inconsistency of findingsacross different studies. Although many studies reportedsignificant correlations between reading-related skills andauditory skills (e.g., [1,2,4-17]), others failed to find suchcorrelations [18-25]. More specifically, whereas in severalstudies, pitch processing was found to account for significant

variance in reading skills (e.g., [1,9,17]), this was not the casein other studies (e.g., [25,26]). This discrepancy was attributedto differences in the types of perceptual tasks used [27-29] orto differences in the characteristics of the sampled populations[12,30]. Here, we consider an additional factor - the potentialcontribution of musical experience to the relationships betweenauditory processing and reading-related skills. Specifically, weask whether musical training affects both auditory processingand reading related skills in a similar manner, and with similartime constants.

It is well documented that individuals with long-term musicalexperience have better auditory skills than non-musicians(reviewed in 31). Musicians’ performance is better than that ofindividuals with no musical experience in analyzing both trained

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and untrained acoustic features. They are better indiscriminating trained melodic relationships, and in fine-graineddiscrimination of basic acoustic features such as pitch [32,33]and duration [34,35]. Those perceptual advantages areaccompanied by group differences in cortical (e.g., [36] andsee 37 for review) and subcortical (e.g., [38-40]) processing ofsound. A longitudinal study in which children were pseudo-randomly assigned to music vs. non-music groups suggeststhat even relatively short-term musical training (~one year)results in enhanced behavioral sensitivity to small pitchvariations in speech [41]. It seems that such training alsoinduces modifications in the neural encoding of sound becausegreater changes in electrophysiological indices of auditoryfunction were found in children taking music lessons than inage matched children not taking such lessons [42,43]. Studiesin which individuals with different amounts of musical trainingwere compared suggest that even individuals with relativelyshort-term musical experience have enhanced auditoryprocessing in a musical context when compared with non-musicians [44-47], though the extent of generalization to puretone discriminations was not directly assessed.

In contrast to the relatively clear effects of musicalexperience on auditory processing, the effects of musicaltraining on other cognitive and language skills are still debated[44,48,49]. For example, longitudinal studies suggest that a fewyears of musical training can positively contribute to verbal (butnot visual) memory [50,51], and to reading of inconsistent (butnot regular) words [41]. More refined neural processing oflinguistic pitch patterns in tonal languages is found inmusicians, even when they are not speakers of a tonallanguage [52,53]. On the other hand, a meta-analysis of 6studies, in which children were randomly assigned to groupsthat either received or did not receive music lessons, failed tofind a consistent effect of music lessons on indices of readingperformance [48].

More consistent broader benefits putatively associated withmusical experience were shown when individuals with intensivelong-term musical training (i.e. musicians) were assessed. Inaddition to enhanced auditory perception [33,34,54], studiesreport enhanced sensory-motor [55-57], linguistic [58] andcognitive [44,50,59-61] skills. These are accompanied bychanges in brain function (see 31,62,63 for reviews). Thoughcausality is typically not directly shown, the common findingthat the magnitude of these benefits is correlated with thenumber of years of musical training and is larger with an earlieronset of practice supports this interpretation. Nevertheless, thealternative, that more motivated or more talented individualsstart playing at an earlier age and continue to play longer thanless motivated/talented ones, cannot be ruled out becauserandomly assigned groups were not (yet) followed long-term.

Thus, while the literature suggests that the impact ofprolonged musical practice is partially generalized to othercognitive skills, the dynamics of this generalization is far fromunderstood. Perhaps auditory perception, which is tightly linkedwith musical training, is immediately improved by musicalpractice whereas linguistic skills, which are related onlyindirectly, improve only subsequently, in a cascade manner. Ifmusical training has a larger and/or faster influence on auditory

perception than on reading-related cognitive skills, it will atleast initially, reduce the observed correlations between thesetwo domains. Yet, to the best of our knowledge, musicalexperience was not considered in any of the above mentionedstudies. In fact, we are aware of only one study that assessedthe possible influence of musical training on the pattern ofcorrelations between auditory and reading skills [64]. In thisstudy, pitch, rhythm and timbre discrimination were assessed inaddition to phonological awareness and word identificationskills. It was found that pitch discrimination was correlated withphonological awareness and with accuracy of single wordreading in children with no musical experience, but not amongchildren with an average of 2 years of musical experience. Thisstudy suggests that musical experience may indeed initiallyreduce the observed pattern of correlations between auditoryperception and reading related skills. However, given therelatively small group of musically trained children (n=26), theirbroad range of musical education (0.5-5 years) and their broadage range (5-9 years old), its findings are mainly suggestive.To study these relationships systematically, we recruited acommunity sample of 184 children from a restricted age range(third grade). We characterized auditory discriminations(frequency and temporal-interval), memory and reading skillsas a function of the amount of formal musical education (noneto 3 years). We then separately calculated the correlationsbetween these skills in groups with different amounts inmusical training.

Materials and Methods

1: Participants184 third-grade children (mean age 8; 8±0; 4) from three

mainstream public schools participated in this study. Based onparent and teacher reports children were typically developingwith no history of hearing or neurological problems. Fifteenchildren failed to provide information about their musicalbackground and were therefore excluded from the study.Additional 13 children failed to complete parts of the testingprotocol due to time constraints or technical problems, andtheir data were excluded from data analysis. Of the remaining156 children, 108 were taking music lessons at the time of thestudy and are thus referred to as ‘musically experienced’. Theremaining children never participated in any form of formalmusic lessons and are thus referred to as ‘musically naïve’.‘Musically experienced’ children were taking formal musiclessons for 1-36 months (mean 13±9 months). Musicallyexperienced children were taking weekly music lessons,learning to play an instrument -- most typically piano orrecorder

The study was approved by the ethics committee of theDepartment of Psychology of the Hebrew University. Datacollection in schools was approved by the chief scientist in theMinistry of Education and was conducted according to theirguidelines. Written consent was obtained from the parents ofall children prior to data collection.

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2: Stimuli and TasksAuditory psychophysical tasks. Frequency and temporal-

interval discrimination were assessed using adaptive (3-down/1-up) auditory discrimination tasks designed to track the79% correct point on the psychometric function. Eachprocedure began with an oral explanation, followed by 10 easy(using only the largest inter-tone difference) practice trials. Ifthe participant performed less than 8/10 correct, he/she wasgiven 10 additional training trials. The subsequentlyadministered assessment blocks, from which thresholds werecomputed, were 80 trials long.

Frequency Discrimination. Two 200 msec pure tones werepresented in each trial and children had to determine whichone was higher – the first or the second. The first tone (thereference) was always 1000 Hz, whereas the frequency of thesecond tone (the test tone) was adapted based on theresponses of the listener. The initial frequency differencebetween the reference and the test tones was 50%.Subsequently the frequency difference decreased/increased ina 3-down/1-up staircase. During the staircase procedure, stepsize was decreased every 4 reversals, as follows: For the first 4reversals the frequency differences were halved/doubled;subsequently the frequency difference was divided/multipliedby 1.4, 1.1 and 1.05. This task was completed by a total of 156children, of whom 108 were taking music lessons at the time ofthe study.

Temporal-Interval Discrimination. Two pairs of 50-msec 1-kHz tones were played on each trial and children had to selectthe pair defining the longer interval- the first or the second. Thefirst interval (the reference) was always 375 msec (offset toonset), whereas the second (the test) interval was adaptedbased on the responses of the listener, beginning with a 50%difference. On subsequent trials, the duration of the testinterval was adapted in a procedure identical to that describedfor the frequency discrimination task. This task was completedby 108 of the children who completed the frequencydiscrimination task, 68 of whom were taking music lessons atthe time of the study.

The tasks were administered through the built-in soundcardof a laptop and circumaural headphones (JTS HP-535). Agraphical interface created in Flash was used to present thesounds, run the adaptive procedure and collect listeners’responses. To experience the interface, visit: http://papi.huji.ac.il/Default.aspx. In both tasks inter-stimulus intervalwas 1000 msec. Listeners could make their response as soonas the second tone ended and there was no time limit on theresponse interval. Inter-trial-interval was 500 msec from theresponse made by the subject.

Calculation of discrimination thresholds (Just NoticeableDifference, JND). Participants in this study had 9-19 reversalsin each block of 80 trials. These numbers are consistent withour previous studies in both children and adults [12,28,65,66].Therefore, raw JNDs were calculated as the mean frequency orduration differences between the reference and non-referenceintervals in the last 7 reversals of each block. JNDs were logtransformed so that a discrimination threshold of 1% (i.e. afraction of 0.01) translates to a log value of -2, whereas adiscrimination threshold of 10% translates to a log value of -1.

Log transforms were used to normalize the distribution of JNDsand allow for the use of parametric statistics.

Reading. Decoding pointed Hebrew words and pseudo-words was tested using the lists developed by Deutsch andBentin [67]. Reading accuracy was defined as the meanpercent correct across the two lists; reading duration wasdefined as the average reading duration (in seconds) acrossthe two lists.

Reading-related skills. Verbal Memory was assessedusing the standard Digit span task (Wechsler, 1998; Israeliedition [68]). In this task, participants listen to increasinglylonger lists of digits read by the experimenter and repeat themin order of presentation (Digit forward) or in reversed order(Digit backwards). The number of correctly recalled lists in theforward part was used as an index of memory span. The totalnumber of correctly recalled lists in the backward subtest wasused as an index of working memory.

Phonological Awareness. A (CV or CVC) syllable deletiontask containing 12 items was used. Participants were read aword and were asked to produce the word without a specificsyllable, the first (4 items), the middle (5 items), or the last one(3 items) (e.g. "/Ra-ashan/ without /Ra/" -> /Ashan/).

General reasoning abilities. General reasoning abilitieswere assessed using Raven’s Standard Progressive Matrices[69]. In this test, arrays of visual objects, each with a missingone, are presented. Participants are asked to complete eacharray by selecting from six alternatives.

3: Testing procedureChildren were tested individually, in a quiet room in each

school. Two sessions, each lasting 45 minutes (one schoolperiod) were administered to each participant few days apart.Children were tested with psychophysical and non-psychophysical tasks in an interleaved manner. On the firstsession children were tested on frequency discrimination,Raven’s matrices and word reading. Temporal-intervaldiscrimination, non-word reading, verbal memory andphonological awareness were tested on the second session.

4: Data analysisAn inspection of the skewness and kurtosis of all the

variables within our data set suggested that the distributionswere approximately normal. Therefore, parametric statisticswere used in all subsequent analyses. Pearson and partialcorrelations were used to evaluate the relationships betweenindices of auditory processing on the one hand and reading-related skills on the other. To determine whether children withdifferent amounts of musical experience differed on any of theauditory processing or reading-related measures, children weredivided to groups with different amounts of musical experience(see Sections 3.2 and 3.3 below), and planned comparisons(contrasts) were use to compare each of the groups withmusical experience to the ‘no experience’ group. With theexception of Raven’s matrices, variance in all other variableswas homogeneous across groups (Levene’s statistic < 2.2, p >0.09).

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Results

1: Frequency discrimination, verbal memory andreading-related skills

Modest but significant correlations were observed betweenfrequency discrimination on the one hand and reading relatedmeasures on the other hand (n=156). These include wordreading, verbal memory and phonological awareness (Table 1,left columns). A similar pattern of correlations was foundbetween temporal-interval discrimination and reading relatedmeasures (a subgroup of 108 children; Table 1, right columns).Both types of auditory thresholds were more highly correlatedwith measures of verbal memory, which, unlike reading andphonological awareness, is not directly taught in schools.Auditory thresholds, as well as verbal memory andphonological awareness scores were also correlated with non-verbal visual reasoning abilities (as measured by the Ravenmatrices). Still, as shown in Table 1, the use of partialcorrelations to account for the statistical contribution of Ravenmatrices to the observed correlations did not substantially alterthe pattern of correlations between auditory and reading-related measures. This indicates that the associations betweenperceptual and language skills are not a mere outcome of thecontribution of general abilities to performance in bothdomains.

Table 1. Correlations between auditory discrimination,cognitive and literacy related skills.

Frequencydiscrimination (log JND)N=156

Temporal-interval discrimination(log JND) N=108

Pearson

Partial(controlling forRaven) Pearson

Partial(controllingfor Raven)

Readingaccuracy(%correct)

-0.21** -0.16* -0.17 -0.14

Reading rate(duration of

reading the list)0.18* 0.18* -0.03 -0.05

Memory span(digit forward)

-0.33*** -0.22** -0.34*** -0.24*

Working memory(digit backward)

-0.20* -0.08 -0.39*** -0.29**

Phonologicalawareness(accuracy)

-0.26** -0.17* -0.29** -0.24*

Cognitive skill(Raven)

-0.36*** − -0.33** −

*p < 0.05; **p < 0.01; ***p < 0.001doi: 10.1371/journal.pone.0075876.t001

2: The relationships between musical experience andtask performance

General cognitive ability, verbal memory span, frequencyand temporal-interval discrimination thresholds were alsosignificantly correlated with musical experience (quantified astime since the beginning of formal music lessons) of thechildren in our sample (Pearson correlations: Raven: r = 0.24, p= 0.003; Digit forward: r = 0.23, p = 0.004; Frequencydiscrimination: r = -0.34, p < 0.001; Temporal-intervaldiscrimination: r = -0.22, p = 0.022).

To take a closer look at the differences between children withdifferent amounts of musical experience, the 156 children whocompleted both frequency discrimination and the reading andreading-related tasks were divided into 4 groups based on thetime they were taking music lessons: one group (n = 48) neverengaged in any formal music training. The remaining groupshad 1-6, 7-12 or more than 12 months of music lessons (n =45, 22 and 41, respectively). Analyses of variance with musicalexperience as a between subject factor revealed significantgroup differences in frequency discrimination (F(3,152) = 5.64,p = 0.001), memory span (F(3,152) = 3.16, p = 0.026) andRaven scores (F(3,152) = 4.16, p = 0.007), as illustrated inFigure 1. Other measures, like working memory, phonologicalawareness and reading rate and accuracy, were notsignificantly different between the groups. Contrast analysescomparing each of the groups with musical experience to the‘no experience’ group show that the group with more than 1-year of musical experience had significantly lower (better)frequency discrimination thresholds (t(152) = 4.04, p < 0.001,Cohen’s d = 0.86, Figure 1, top left), longer memory spans(t(152) = -3.03, p = 0.003, Cohen’s d = 0.65, Figure 1, top,second panel from left) and higher Raven scores (t(73.24) =-3.64, p < 0.001, Cohen’s d = 0.61). In fact, even the group withonly 1-6 months of musical training had higher Raven scoresthan the ‘no experience’ group (t(88.51) = -1.91, p = 0.03; seeFigure 1, bottom row, rightmost panel).

A similar analysis was conducted on the temporal intervaldiscrimination thresholds of the 108 children who completedthis task (Figure 1, bottom, left). Although the omnibus ANOVAwas nonsignificant, the planned contrast analysis suggestedthat the group with more than 1 year of musical experiencetended to have lower thresholds than the ‘no experience’ group(t(108) = 1.95, p = 0.054), albeit with a small effect size(Cohen’s d = 0.36).

The current data are consistent with previous studies thatreported differences in IQ as a function of musical experience.Generally, IQ differences in relation to musical experience areattributed to the fact that children with higher IQs are morelikely to study music rather than to causal effects of training[70]. Indeed, the difference in Raven scores between childrenwith and without musical experience makes it hard todetermine whether other differences are simply attributable topre-existing IQ differences that make some children more likelythan others to study music and to have better perceptual andmemory skills. To account for these effects, the group analysiswas repeated while statistically accounting for IQ differences byusing Raven scores as covariates. This analysis left the groupdifferences in frequency discrimination significant (F(3,152) =

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3.46, p = 0.018), but obliterated the effects on memory spans(F(3,152) = 1.91, p = 0.131). Therefore, it appears thatwhereas the effect of short-term musical experience onauditory frequency discrimination cannot be fully attributed todifferences in general reasoning skills, the longer memoryspans in musically trained children (at least with the limitedexperience of the children in the current study) may reflectbroader, pre-existing IQ differences.

3: The pattern of correlations between auditorydiscrimination and reading-related skills amongchildren with different amounts of musical experience

The correlations between frequency and temporal-intervaldiscrimination on the one hand and reading related skills on theother hand, were calculated separately for children with nomusical experience (n=40), and for children with more than oneyear of musical experience (n=26).

Figure 2 shows memory spans (left) and working memory(right) as a function of frequency discrimination in the groupswith (bottom) and without (top) musical experience. The scatterplots suggest a different distribution of performance betweenthe groups. Most salient is the difference in frequencydiscrimination thresholds. Among individuals with no musicalbackground the proportion of very poor performers (denoted by

the vertical line; thresholds > -1, i.e. larger than 10%) is muchhigher than that among individuals with more than one year oftraining (Fisher’s exact test: p = 0.001). Importantly, theseparticipants, with no musical experience and poor frequencydiscrimination tend to have lower memory spans (Figure 2, topleft panel) and lower working memory span (Figure 2, top rightpanel). A similar pattern was observed for temporal-intervaldiscrimination, as shown in Figure 3, although it was notsignificant. These findings indicate that participants who had nomusical experience were more likely to have poor frequencydiscrimination, which were associated with generally poorverbal memory spans. Further research is required todetermine whether this is also the case for temporal-intervaldiscrimination. We should note that this group of poorperformers had a similar contribution from each of the 3schools that took part in this study, suggesting that this linkageis not an outcome of inter-school cultural/educationaldifferences.

Table 2 shows that the pattern of correlations betweenauditory processing on the one hand and reading and reading-related measures on the other is indeed different in these twogroups. While in the musically naïve group, the correlationswith both measures of auditory processing are significant, theyare not significant among individuals with more than one year

Figure 1. Auditory perception (frequency and interval discrimination), verbal memory (Digit forward and Digit Backward)and reasoning ability (Raven’s matrices) as a function of musical experience, in months of formal training. Error bars are ±1 standard error of the mean.doi: 10.1371/journal.pone.0075876.g001

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of musical training. To assess the significance of this reductionin correlations, we calculated 95% confidence intervals (CI) forthe significant correlations in the no-experience group using abootstrapping procedure (CI columns in Table 2). Groupdifferences were considered significant (and correlations weremarked in bold) if the correlation for the more experiencedgroup fell outside of this confidence interval. This analysisshows that the correlations between temporal-intervaldiscrimination and the rest of the measures (cognitive skills,reading accuracy, memory span and working memory) wereindeed significantly stronger in the group with no musicalexperience (the two leftmost columns in Table 2). Amongmusically naïve participants, partial correlations (controlling forthe Raven scores) between temporal-interval discriminationthresholds and reading-related skills remained significant andsimilar in magnitude to the Pearson correlations (readingaccuracy: -0.37, p = 0.022; memory span: r = -0.44, p = 0.005;working memory: r = -0.49, p = 0.002; phonological awareness:r = -0.36, p = 0.02). Therefore it appears that in this group, thecorrelations between auditory discriminations and reading-

related skills are genuine and cannot be accounted for bygeneral cognitive skills.

Discussion

We found that both frequency discrimination and intervaldiscrimination are correlated with reading-related skills, asreported previously (e.g., [4,6,7,9,12,17]). These correlationsremained significant when covariance with reasoning ability(assessed with Raven’s Matrices, a visual-spatial test) wascontrolled for. However, these correlations differed betweenchildren with different amounts of musical training. In "musicallynaïve” listeners there were significant correlations betweenfrequency and temporal-interval discrimination on the one handand reading accuracy, phonological awareness, verbal memoryworking memory on the other hand. These correlations reflectthe abundance of individuals with poor auditory discriminationscores, who tend to have poor verbal memory scores. Theproportion of individuals with poor auditory discriminationthresholds in the group with more than a year of musical

Figure 2. Scatter plots illustrating the relationships between frequency discrimination and two aspects of verbal memory,simple span (Digit forward; left column) and working memory span (Digit backward; right column) in musically naïve (toppanels) and in musically experienced (more than a year; bottom panels) children. Dashed lines show the linear relationshipsbetween memory and frequency discrimination. Note that among musically trained children the JNDs of only 3/26 children werepoorer than 10% (corresponding to a value of -1 in log units) whereas among musically naïve individuals 18/40 had these poorthresholds. In both groups these individuals tend to have poor memory scores.doi: 10.1371/journal.pone.0075876.g002

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training is much smaller. In this group, these correlationsdisappeared. While on average, this group had significantlylower frequency discrimination thresholds, and to a certainextent better temporal-interval discrimination, the distribution ofthresholds mainly reflects a lack of very poor performers, ratherthan a clear over representation of very good performers.Together these findings suggest that a relatively small amountof musical training suffices to improve basic perceptual skills,particularly among initially poor performers, but does notimmediately generalize to verbal and cognitive skills in thebroader population of musically trained participants.

Although musically experienced children had betterfrequency discrimination thresholds even after their somewhatlower Raven scores were taken into account, the correlationaldesign of the study makes it impossible to rule out analternative interpretation for the relative scarcity of poorauditory processing in musically experienced children, namelythat children with poorer auditory skills are simply less likely totake music lessons, although we find this less likely for thefollowing reasons. First, musically experienced children in thecurrent study were taking music lessons as part of an after-

school activity in their schools. These after school programs donot screen participants for musical (or any other) aptitude.Therefore it seems less likely that children with poorer auditoryskills were actively discouraged from taking music lessons,although they may have refrained from taking them for otherreasons. Second, although consistent with the pre-existingdifferences account, children with any amount of musicalexperience had higher Raven scores than the musically naïvechildren, this was not the case for auditory processing. Hadpre-existing differences in auditory processing, general abilityor motivation been the cause of the observed differencesbetween musically naïve and musically experienced children,we would expect auditory differences even between the naïveparticipants and those with 1-12 months of musical training. Asshown in Figure 1, this was not the case.

1: Patterns of correlationsThe present findings suggest that part of the controversy

regarding the association between auditory processing andreading-related skills may be resolved by accounting forparticipants’ degrees of musical experience, which was not

Figure 3. Scatter plots illustrating the relationships between temporal-interval discrimination and two aspects of verbalmemory, simple span (Digit forward; left) and working memory (Digit backward; right) in musically naïve (top panels) andmusically experienced (more than a year of training; bottom panels) children. Among musically naïve children 10/40 havepoor (> 50%) thresholds (right of the vertical lines denoting JND = -0.3). These children tend to have poorer memory spans,particularly poor working memory span (top right panel).doi: 10.1371/journal.pone.0075876.g003

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considered in most previous studies. This conclusion isconsistent with the one previous study in which musicalexperience was considered as an independent variable in theanalysis of the relationships between auditory processing(pitch, rhythm and timbre discrimination) and reading-relatedskills (word identification and phonological skills) [64]. Takentogether, it thus seems that in “musically naïve” children ofsimilar ages and reading instruction, auditory processing isconsistently related to reading-related skills, and that the lackof associations reported in earlier studies (e.g., [20,23]) mayresult from testing samples with mixed musical experience,perhaps with a large representation of children with musicalbackground. Indeed, in previous studies in which school-agechildren were tested on both frequency discrimination andreading-related tasks [1,17,26], the proportions of variance inreading-related scores accounted for by frequencydiscrimination ranged from 0 to 0.25 (i.e. correlations rangingfrom 0 to .5). The correlations observed in the present study(see Table 1), are consistent with those findings, withfrequency discrimination statistically accounting for 4% of thevariance in reading accuracy, 6% of the variance inphonological awareness and 11% of the variance in memoryspans. Among the musically naïve children in the current study(Table 2), frequency discrimination accounted for 9%, 10%,11% and 13% of the variance in word reading, phonologicalawareness, memory spans and working memory, respectively.Interestingly, those values are similar in magnitude to thecontribution of pitch processing to reading as reported for pre-school children (9%) [9]. Assuming that younger children areless likely to receive formal music training, it might therefore bethat those values reflect the ‘true’ unique contribution offrequency discrimination to reading.

Interestingly, the magnitude of the effect was even larger forinterval discrimination, where thresholds in musically naïve

Table 2. Inter skill correlations in the sub-groups with (morethan 12 months) and without musical training.

Frequency DiscriminationTemporal-intervalDiscrimination

Musicexperience(months) 0(n=40) >12(n=26) 0(n=40) >12(n=26) r CI r r CI rCognitive skill -0.28 -0.06 -0.32* -0.62-0.04 0.06Readingaccuracy

-0.31* -0.56 0.08 -0.10 -0.38* -0.62-0.02 0.22

Reading rate 0.01 0.19 0.12 0.03Memoryspans

-0.34* -0.59-0.03 -0.34 -0.51** -0.78-0.15 -0.09

Workingmemory

-0.37* -0.62-0.07 -0.22 -0.56*** -0.73-0.32 -0.09

Phonologicalawareness

-0.32* -0.56-0.02 -0.17 -0.42** -0.68-0.11 -0.13

*p < 0.05; **p < 0.01; ***p < 0.001. Correlation values that are marked with boldtypeface denote values that fall outside the CI of musically naïve participants.doi: 10.1371/journal.pone.0075876.t002

participants accounted for more than 30% of the variability inworking memory spans. Yet, a corresponding analysis fortemporal-interval discrimination is currently not feasiblebecause the relationships between temporal-intervaldiscrimination and reading were not as intensively studied inschool-age children (though see 1 for a similar finding inSpanish speaking children).

2: Dynamics of improvement in frequency versustemporal-interval discrimination

Adults with long and intensive musical training attainsubstantially better thresholds than those we measured[32-34]. Nevertheless the current data suggest that evenrelatively minimal musical experience is associated with betterfrequency discrimination. Although the current data are alsoconsistent with the idea that even individuals with relativelybrief (~ 1 year) experience with formal music lessons havebetter temporal-interval discrimination than musically naïveones, this effect was more subtle and manifested in changes tothe pattern of correlations between temporal-intervaldiscrimination and reading-related skills, and not in a change tomean discrimination thresholds. Since previous studies,conducted among highly experienced musicians, suggest thatthey have better temporal-interval discrimination thresholds[34,35], genuine threshold improvements seems to requiremore than a few months of musical training. Several reasonscould account for the different time courses of frequency andtemporal-interval discrimination. First, temporal-intervaldiscrimination might be more resilient to modification thanfrequency discrimination. This however seems unlikely giventhe outcomes of studies in which naïve listeners were trainedon either frequency or temporal-interval discrimination [15,33],because in those studies the learning profiles on the two tasksdid not drastically differ in terms of the number of training daysor the total number of trials required for learning. Alternatively,the initial stages of formal music learning may place a greateremphasis on skills involving pitch than on those involvingrhythm thereby resulting in faster changes in frequency than intemporal-interval discrimination.

3: Dynamics of generalization to reading-relatedlanguage skills

Previous studies reported that musicians’ verbal memoryspans are larger than those of non-musicians [50,51,60], andthat years of practice are correlated with verbal memory. Otherstudies that assessed the relations between verbal memoryand musical experience, also studied populations with longerperiods of musical training [71,72]. The current data suggestthat one year of formal music training of the type characteristicof most (Israeli) children, that is taking music lessons as anafter school activity, is not enough to induce a significantgeneralization to non-auditory skills. Although musicallyexperienced children tended to have higher memory scoresthan their musically naïve peers, the effect was small and wecould not tease it apart from the effects of the somewhat highergeneral cognitive skills in the musically experienced group. Themost likely interpretation of this finding is that longer and/ormore intensive musical training is required to drive changes in

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verbal memory than in pitch discrimination. This interpretationis in line with findings of a longitudinal study where musicallyexperienced children with an average experience of 2.5 yearshad better verbal memory than children with no musicalexperience. When those children were followed longitudinally,their memory scores continued to improve with further musicalpractice, but not if they stopped taking music lessons [50].

In contrast to the weak relationships between musicalexperience and memory among individuals with average orabove auditory skills, we found that both memory spans andworking memory were particularly poor among children withpoor auditory discriminations (Figures 2, 3). These childrenwere quite prevalent in the “musically naïve” group, but quiterare in the musically trained group. Assuming that thedistribution of auditory skills was initially similar in the twogroups, this finding suggests that children with initially poorauditory processing might gain the most from relatively smallamounts of training, with perhaps a broader initial transfer tolanguage related skills. An earlier study we conducted inindividuals with dyslexia and poor working memory suggeststhat this may indeed be the case. In that study [15], individualswith initially poor auditory processing and poor workingmemory were trained on frequency and duration discriminationuntil their performance on these tasks reached that of theiradequately reading peers. Their perceptual learninggeneralized to improved verbal working memory (adequateDigit backward), and both perceptual and memory gainsremained stable for at least few months after the end oftraining, when they were re-tested. Importantly, a relativelyshort period of practice was sufficient, suggesting that perhaps,short practice is sufficient to drive working memory changeswhen initial performance is very poor. Since children with poorauditory processing may be less likely to receive formal musicinstruction (at least in places where music lessons are notmandatory), future studies should specifically target thispopulation.

Taken together, these findings suggest that generalizationmay be more immediate among individuals with initially verypoor performance, compared with individuals with better initialthresholds, where evidence for broader improvement is mainlyfound after years of practice. Perhaps this putative difference

reflects different learning mechanisms. Improvement amongvery poorly performing individuals may stem fromstrengthening broader top-down mechanisms [73], maybeimproving a more general ability to sustain auditory attention,which is probably not the bottleneck limiting performance ofindividuals with better thresholds.

Conclusions

Although the correlational design of the current study makesit impossible to reach definitive conclusions regarding thecausal contribution of musical training to cognition, it highlightstwo important issues. First, the pattern of correlations betweenperceptual and non-perceptual skills differs between musicallynaive individuals and those with even relatively short musicaltraining, a factor that was not taken into account in earlierstudies. Second, the changes we associate with musicalexperience are not simultaneous and uniform changes acrossdomains, or across populations. Rather, we tentatively proposethat musical training readily and rapidly generalizes tofrequency discrimination, then to interval discrimination, andonly subsequently to enhanced language and memory skills.Moreover, the degree of generalization may depend on initialauditory performance, being perhaps broader among initiallypoor performers. Further studies in which children arerandomly assigned to receive (or not receive) musical trainingand then followed over time are required to test this proposal.Nevertheless, the present findings suggest that baselineauditory processing should be considered when attempting touse and evaluate music as a form of intervention.

Acknowledgements

We thank Noa Nutkevitch, Rahav Gabai and Amihai Rigbi fororganizing and administering this study.

Author Contributions

Conceived and designed the experiments: MA. Analyzed thedata: KB. Wrote the manuscript: MA KB.

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